[26] | 1 | /*************************************************************************/ |
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| 2 | /* */ |
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| 3 | /* Evaluation of a test on a continuous valued attribute */ |
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| 4 | /* ----------------------------------------------------- */ |
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| 5 | /* */ |
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| 6 | /*************************************************************************/ |
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| 7 | |
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| 8 | |
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| 9 | #include "buildex.i" |
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| 10 | |
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| 11 | |
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| 12 | float |
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| 13 | *SplitGain, /* SplitGain[i] = gain with att value of item i as threshold */ |
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| 14 | *SplitInfo; /* SplitInfo[i] = potential info ditto */ |
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| 15 | |
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| 16 | |
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| 17 | |
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| 18 | /*************************************************************************/ |
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| 19 | /* */ |
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| 20 | /* Continuous attributes are treated as if they have possible values */ |
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| 21 | /* 0 (unknown), 1 (less than cut), 2(greater than cut) */ |
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| 22 | /* This routine finds the best cut for items Fp through Lp and sets */ |
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| 23 | /* Info[], Gain[] and Bar[] */ |
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| 24 | /* */ |
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| 25 | /*************************************************************************/ |
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| 26 | |
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| 27 | |
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| 28 | EvalContinuousAtt(Att, Fp, Lp) |
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| 29 | /* ----------------- */ |
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| 30 | Attribute Att; |
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| 31 | ItemNo Fp, Lp; |
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| 32 | { |
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| 33 | ItemNo i, BestI, Xp, Tries=0; |
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| 34 | ItemCount Items, KnownItems, LowItems, MinSplit, CountItems(); |
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| 35 | ClassNo c; |
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| 36 | float AvGain=0, Val, BestVal, BaseInfo, ThreshCost, |
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| 37 | ComputeGain(), TotalInfo(), Worth(); |
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| 38 | void Swap(); |
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| 39 | |
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| 40 | Verbosity(2) printf("\tAtt %s", AttName[Att]); |
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| 41 | Verbosity(3) printf("\n"); |
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| 42 | |
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| 43 | ResetFreq(2); |
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| 44 | |
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| 45 | /* Omit and count unknown values */ |
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| 46 | |
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| 47 | Items = CountItems(Fp, Lp); |
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| 48 | Xp = Fp; |
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| 49 | ForEach(i, Fp, Lp) |
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| 50 | { |
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| 51 | if ( CVal(Item[i],Att) == Unknown ) |
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| 52 | { |
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| 53 | Freq[ 0 ][ Class(Item[i]) ] += Weight[i]; |
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| 54 | Swap(Xp, i); |
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| 55 | Xp++; |
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| 56 | } |
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| 57 | } |
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| 58 | |
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| 59 | ValFreq[0] = 0; |
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| 60 | ForEach(c, 0, MaxClass) |
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| 61 | { |
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| 62 | ValFreq[0] += Freq[0][c]; |
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| 63 | } |
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| 64 | |
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| 65 | KnownItems = Items - ValFreq[0]; |
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| 66 | UnknownRate[Att] = 1.0 - KnownItems / Items; |
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| 67 | |
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| 68 | /* Special case when very few known values */ |
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| 69 | |
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| 70 | if ( KnownItems < 2 * MINOBJS ) |
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| 71 | { |
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| 72 | Verbosity(2) printf("\tinsufficient cases with known values\n"); |
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| 73 | |
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| 74 | Gain[Att] = -Epsilon; |
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| 75 | Info[Att] = 0.0; |
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| 76 | return; |
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| 77 | } |
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| 78 | |
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| 79 | Quicksort(Xp, Lp, Att, Swap); |
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| 80 | |
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| 81 | /* Count base values and determine base information */ |
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| 82 | |
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| 83 | ForEach(i, Xp, Lp) |
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| 84 | { |
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| 85 | Freq[ 2 ][ Class(Item[i]) ] += Weight[i]; |
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| 86 | SplitGain[i] = -Epsilon; |
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| 87 | SplitInfo[i] = 0; |
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| 88 | } |
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| 89 | |
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| 90 | BaseInfo = TotalInfo(Freq[2], 0, MaxClass) / KnownItems; |
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| 91 | |
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| 92 | /* Try possible cuts between items i and i+1, and determine the |
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| 93 | information and gain of the split in each case. We have to be wary |
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| 94 | of splitting a small number of items off one end, as we can always |
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| 95 | split off a single item, but this has little predictive power. */ |
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| 96 | |
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| 97 | MinSplit = 0.10 * KnownItems / (MaxClass + 1); |
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| 98 | if ( MinSplit <= MINOBJS ) MinSplit = MINOBJS; |
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| 99 | else |
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| 100 | if ( MinSplit > 25 ) MinSplit = 25; |
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| 101 | |
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| 102 | LowItems = 0; |
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| 103 | ForEach(i, Xp, Lp - 1) |
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| 104 | { |
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| 105 | c = Class(Item[i]); |
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| 106 | LowItems += Weight[i]; |
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| 107 | Freq[1][c] += Weight[i]; |
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| 108 | Freq[2][c] -= Weight[i]; |
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| 109 | |
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| 110 | if ( LowItems < MinSplit ) continue; |
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| 111 | else |
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| 112 | if ( LowItems > KnownItems - MinSplit ) break; |
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| 113 | |
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| 114 | if ( CVal(Item[i],Att) < CVal(Item[i+1],Att) - 1E-5 ) |
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| 115 | { |
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| 116 | ValFreq[1] = LowItems; |
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| 117 | ValFreq[2] = KnownItems - LowItems; |
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| 118 | SplitGain[i] = ComputeGain(BaseInfo, UnknownRate[Att], 2, KnownItems); |
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| 119 | SplitInfo[i] = TotalInfo(ValFreq, 0, 2) / Items; |
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| 120 | AvGain += SplitGain[i]; |
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| 121 | Tries++; |
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| 122 | |
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| 123 | Verbosity(3) |
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| 124 | { printf("\t\tCut at %.3f (gain %.3f, val %.3f):", |
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| 125 | ( CVal(Item[i],Att) + CVal(Item[i+1],Att) ) / 2, |
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| 126 | SplitGain[i], |
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| 127 | Worth(SplitInfo[i], SplitGain[i], Epsilon)); |
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| 128 | PrintDistribution(Att, 2, true); |
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| 129 | } |
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| 130 | } |
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| 131 | } |
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| 132 | |
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| 133 | /* Find the best attribute according to the given criterion */ |
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| 134 | |
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| 135 | ThreshCost = Log(Tries) / Items; |
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| 136 | |
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| 137 | BestVal = 0; |
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| 138 | BestI = None; |
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| 139 | ForEach(i, Xp, Lp - 1) |
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| 140 | { |
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| 141 | if ( (Val = SplitGain[i] - ThreshCost) > BestVal ) |
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| 142 | { |
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| 143 | BestI = i; |
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| 144 | BestVal = Val; |
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| 145 | } |
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| 146 | } |
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| 147 | |
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| 148 | /* If a test on the attribute is able to make a gain, |
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| 149 | set the best break point, gain and information */ |
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| 150 | |
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| 151 | if ( BestI == None ) |
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| 152 | { |
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| 153 | Gain[Att] = -Epsilon; |
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| 154 | Info[Att] = 0.0; |
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| 155 | |
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| 156 | Verbosity(2) printf("\tno gain\n"); |
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| 157 | } |
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| 158 | else |
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| 159 | { |
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| 160 | Bar[Att] = (CVal(Item[BestI],Att) + CVal(Item[BestI+1],Att)) / 2; |
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| 161 | Gain[Att] = BestVal; |
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| 162 | Info[Att] = SplitInfo[BestI]; |
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| 163 | |
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| 164 | Verbosity(2) |
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| 165 | printf("\tcut=%.3f, inf %.3f, gain %.3f\n", |
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| 166 | Bar[Att], Info[Att], Gain[Att]); |
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| 167 | } |
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| 168 | } |
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| 169 | |
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| 170 | |
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| 171 | |
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| 172 | /*************************************************************************/ |
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| 173 | /* */ |
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| 174 | /* Change a leaf into a test on a continuous attribute */ |
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| 175 | /* */ |
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| 176 | /*************************************************************************/ |
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| 177 | |
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| 178 | |
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| 179 | ContinTest(Node, Att) |
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| 180 | /* ---------- */ |
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| 181 | Tree Node; |
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| 182 | Attribute Att; |
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| 183 | { |
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| 184 | float Thresh, GreatestValueBelow(); |
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| 185 | ItemCount CountItems(); |
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| 186 | |
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| 187 | Sprout(Node, 2); |
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| 188 | |
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| 189 | Thresh = GreatestValueBelow(Att, Bar[Att]); |
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| 190 | |
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| 191 | Node->NodeType = ThreshContin; |
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| 192 | Node->Tested = Att; |
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| 193 | Node->Cut = |
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| 194 | Node->Lower = |
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| 195 | Node->Upper = Thresh; |
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| 196 | Node->Errors = 0; |
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| 197 | } |
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| 198 | |
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| 199 | |
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| 200 | |
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| 201 | /*************************************************************************/ |
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| 202 | /* */ |
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| 203 | /* Return the greatest value of attribute Att below threshold t */ |
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| 204 | /* */ |
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| 205 | /*************************************************************************/ |
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| 206 | |
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| 207 | |
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| 208 | float GreatestValueBelow(Att, t) |
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| 209 | /* ------------------ */ |
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| 210 | Attribute Att; |
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| 211 | float t; |
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| 212 | { |
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| 213 | ItemNo i; |
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| 214 | float v, Best; |
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| 215 | Boolean NotYet=true; |
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| 216 | |
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| 217 | ForEach(i, 0, MaxItem) |
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| 218 | { |
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| 219 | v = CVal(Item[i], Att); |
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| 220 | if ( v != Unknown && v <= t && ( NotYet || v > Best ) ) |
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| 221 | { |
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| 222 | Best = v; |
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| 223 | NotYet = false; |
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| 224 | } |
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| 225 | } |
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| 226 | |
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| 227 | return Best; |
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| 228 | } |
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